2019 Technology Predictions: It’s All About the Industrial AI Edge: Actionable AI at the Edge

February 13, 2019 &bullet; Brent Haas

If you subtract the steady stream of Facebook Follies from the list of big technology stories in 2018, you’ll notice a lot of the advances are centered around artificial intelligence, developments in chip design, and amassing the power of the Cloud. I propose that 2019 will see these technologies coalesce around a singular purpose: applying actionable AI at the edge.

High-tech analysts at McKinsey recently released a report estimating that hardware value for edge computing could reach as much as $215 billion by 2025. The authors note that “by circumventing the need to access the cloud to make decisions, edge computing provides real-time local data analysis to devices,” thus powering use cases that span almost every business vertical.

Edge computing exploits the sum total of modern hardware and software advancements to enable everything from drone management and autonomous vehicles to precision agriculture, work-site safety tracking, medical monitoring, and back-office task automation. When you couple McKinsey’s hardware study with dramatic business shifts, a picture emerges of just how huge the edge computing movement already is. For example, news that troubled multinational conglomerate GE will spin off its Industrial Internet of Things (IIoT) software portfolio into a $1.2 billion independent company — comprised of industrial edge-enabling assets such as its Predix platform, manufacturing execution systems, and operations performance management divisions proves how seriously the industry is taking the edge computing movement. To quote McKinsey’s blunt assessment, “unlike recent technological advances such as cloud computing, where most gains were captured by just a few major players in the technology sector, edge computing creates opportunities across a breadth of industries.”

While edge computing and enabling technologies are already starting to take the world by storm, I predict that five specific developments will emerge in the coming year:

The actionable Industrial IoT cloud dominance will become a two-horse race between Microsoft and Amazon, and the leader will be determined by who gets better entrenched in the edge hardware. Microsoft and Amazon will not just extend the cloud to the edge, but will make it dirt simple for hardware (such as gateway) vendors to provide “instant-on” edge and cloud services from the two behemoths.

Sensor manufacturers will begin adding compute with edge analytics to sensors. Small analytics engines will be built right into individual sensors; so instead of the traditional connect-the-sensor to a board or gateway, these new “compute sensors” will have embedded analytics and supply analytics APIs.

Industrial wireless sensor hubs and gateways with built-in edge analytics engines pair-up and quickly become a standard edge tier, called the “sensor hub tier”. This will make a big splash in the Industrial IoT market. Customers will be able to pick and choose “certified” sensors, which come pre-configured and connected. When powered up, users will instantly see the data flowing and preconfigured edge analytics producing insight via their cloud provider of choice.

Artificial intelligence development will democratize into a non-data-scientist phase. Python and machine learning frameworks will still be key for proper data scientists, but Amazon SageMaker and Microsoft Azure Machine Learning Studio will expand the point-and-click path and begin targeting analysts who are “casual” data science practitioners. Accelerators for Industrial IoT sensors which include vibration, temperature, humidity and current will become available in marketplaces for easy training and inferencing at the edge.

Docker will emerge as the “Killer Edge App.” Enterprise loves Docker on the cloud, but containerization is just what we need at the edge. Provisioning and deploying software to the edge is use-case specific, complicated, and can be a security nightmare. Now that edge compute has enough power to run Docker, using it for everything from applications to machine-learning models will become the edge-delivery architecture of choice.

Rest assured that I have no secret personal or professional interest in Amazon or Microsoft or Docker or their edge computing strategies. My predictions are solely based on market potential, existing capability, and obvious applicability toward furthering edge development in scenarios likely to manifest in the very near future.

The actionable Edge AIb revolution is underway; of this I am certain. And regardless of what happens to Facebook, everyone following the technology headlines will be hearing a lot more about it in 2019.